International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 5, No. 12, 8 Nov. 2013
Cover page and Table of Contents: PDF (size: 688KB)
Design a New Fuzzy Optimize Robust Sliding Surface Gain in Nonlinear Controller
Full Text (PDF, 688KB), PP.91-98
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Author(s)
Mohammad shamsodini
1,*
Rouholla Manei
1
Ali Bekter
1
Babak Ranjbar
1
Samira Soltani
2
Index Terms
Classical Control, Non-Classical Control, Fuzzy Logic, Sliding Mode Controller, Sliding Surface Slope, Sliding Mode Fuzzy Controller
Abstract
Control of robotic manipulator is very important in field of robotic, because robotic manipulators are multi-input multi-output (MIMO), nonlinear and most of dynamic parameters are uncertainty. Today, robot manipulators used in unknown and unstructured environment which caused to provides sophisticated systems, therefore strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance (e.g., minimum error, good trajectory, disturbance rejection). One of the best nonlinear robust controller which can be used in uncertainty nonlinear systems, are sliding mode controller but pure sliding mode controller has some disadvantages therefore this research focuses on the design fuzzy sliding mode controller. One of the most important challenging in pure sliding mode controller and sliding mode fuzzy controller is sliding surface slope. This paper focuses on adjusting the sliding surface slope in sliding mode fuzzy controller to have the best performance and reduce the limitation.
Cite This Paper
Mohammad Shamsodini, Rouholla Manei, Ali Bekter, Babak Ranjbar, Samira Soltani, "Design a New Fuzzy Optimize Robust Sliding Surface Gain in Nonlinear Controller", International Journal of Intelligent Systems and Applications(IJISA), vol.5, no.12, pp.91-98, 2013. DOI:10.5815/ijisa.2013.12.08
Reference
[1]Slotine J. J. E., and W. Li., 1991. Applied nonlinear control, Prentice-Hall Inc.
[2]Kurfess T. R, 2005. Robotics and automation handbook, CRC Press.
[3]OKYAY KAYNAK., 2001. Guest Editorial Special Section on Computationally Intelligent Methodologies and Sliding-Mode Control. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 48(1): 2-3.
[4]Wang L. X., 1993. Stable adaptive fuzzy control of nonlinear systems. IEEE Trans. Fuzzy systems, 1(2): 146-154.
[5]Shahnazi R., H. Shanechi, N. Pariz, 2006. Position control of induction and servomotors: A novel adaptive fuzzy PI sliding mode control, IEEE Conferences on power engineering, P.P: 1-9.
[6]Medhaffar H., N. Derbel, and T. Damak, 2006. A decoupled fuzzy indirect adaptive sliding mode controller with application to robot manipulator, Int. Journal on modeling, identification and control, 1(1): 23-29.
[7]Siciliano B, and Khatib O, 2007. Handbook of robotics, Springer.
[8]Emami M. R., Turksen I. B., and Goldenberg A. A., 1998. Development of a systematic methodology of fuzzy logic modelling, IEEE Trans. On fuzzy systems, 6(3):346-361.
[9]Zhang X., and Z. Man, 2000. A new fuzzy sliding mode control scheme, 3rd world congress on intelligent control and automation, P.P: 1692-1696.
[10]Shahnazi R., H. Shanechi, N. Pariz, 2008. Position control of induction and servomotors: A novel adaptive fuzzy PI sliding mode control, IEEE Journals on energy conversions, 23(1): 138-147.
[11]Weng C. C., W. S. Yu, 2008. Adaptive fuzzy sliding mode control for linear time-varying uncertain systems, IEEE conference on fuzzy systems, P.P: 1483-1490.
[12]Yu Z. X, 2009. Adaptive sliding mode-like fuzzy logic control for nonlinear systems, Journal of communication and computer, 6(1): 53-60.
[13]Sh. Tayebi Haghighi, S. Soltani, Farzin Piltan, M. kamgari, S. Zare, “Evaluation Performance of IC Engine: Linear Tunable Gain Computed Torque Controller Vs. Sliding Mode Controller”, International Journal of Intelligent Systems and Applications, 5(6), 2013.
[14]Farzin Piltan, N. Sulaiman, Atefeh Gavahian, Samira Soltani & Samaneh Roosta, “Design Mathematical Tunable Gain PID-Like Sliding Mode Fuzzy Controller with Minimum Rule Base”, International Journal of Robotic and Automation, 2 (3): 146-156, 2011.
[15]Farzin Piltan, N. Sulaiman, S.Soltani, M. H. Marhaban & R. Ramli, “An Adaptive Sliding Surface Slope Adjustment in PD Sliding Mode Fuzzy Control For Robot Manipulator”, International Journal of Control and Automation, 4 (3): 65-76, 2011.
[16]Farzin Piltan, N. Sulaiman, Samaneh Roosta, Atefeh Gavahian & Samira Soltani, “Evolutionary Design of Backstepping Artificial Sliding Mode Based Position Algorithm: Applied to Robot Manipulator”, International Journal of Engineering, 5 (5):419-434, 2011.
[17]Farzin Piltan, N. Sulaiman, Atefeh Gavahian, Samaneh Roosta & Samira Soltani, “On line Tuning Premise and Consequence FIS: Design Fuzzy Adaptive Fuzzy Sliding Mode Controller Based on Lyaponuv Theory”, International Journal of Robotics and Automation, 2 (5):381-400, 2011.
[18]Farzin Piltan, N. Sulaiman, Samira Soltani, Samaneh Roosta & Atefeh Gavahian, “Artificial Chattering Free on-line Fuzzy Sliding Mode Algorithm for Uncertain System: Applied in Robot Manipulator”, International Journal of Engineering, 5 (5):360-379, 2011.
[19]Farzin Piltan, F. Aghayari, M. Rashidian & M.Shamsodini, “A New Estimate Sliding Mode Fuzzy Controller for RoboticManipulator”, International Journal of Robotics and Automation, 3 (1):45-60, 2012.
[20]Farzin Piltan, A. Hosainpour, E. Mazlomian, M.Shamsodini, M.H Yarmahmoudi. ”Online Tuning Chattering Free Sliding Mode Fuzzy Control Design: Lyapunov Approach”, International Journal of Robotics and Automation, 3(3):77-105, 2012.
[21]Farzin Piltan, M.H. Yarmahmoudi, M. Shamsodini, E.Mazlomian, A.Hosainpour. ”PUMA-560 Robot Manipulator Position Computed Torque Control Methods Using MATLAB/SIMULINK and Their Integration into Graduate Nonlinear Control and MATLAB Courses”, International Journal of Robotics and Automation, 3(3): 167-191, 2012.
[22]Farzin Piltan, M.R. Rashidian, M. Shamsodini and S. Allahdadi. ” Effect of Rule Base on the Fuzzy-Based Tuning Fuzzy Sliding Mode Controller: Applied to 2nd Order Nonlinear System”, International Journal of Advanced Science and Technology, 46:39-70, 2012.